Jobs at Snorkel AI

Build and scale machine learning systems for frontier AI data generation and evaluation. Responsibilities include efficient agentic evaluations, model routing, fine-tuning and serving smaller open-weight models, predictive task-difficulty modeling, LLM-as-judge measurement, and productionizing research prototypes. The role requires rigorous experimentation, statistical analysis, strong Python and software engineering, and end-to-end ownership of production ML or software systems.

Advance AI data and agentic environment creation by designing scalable pipelines combining automated generation, real-world data, and expert judgment. Run experiments, evaluate data and model performance, collaborate with engineering, product, customers, and domain experts, and translate research prototypes into production workflows. The role also involves developing expert-authoring workflows, monitoring frontier research, and representing findings through publications, talks, blogs, and customer engagements.

Drafts, reviews, and negotiates customer, vendor, and other commercial agreements. Partners with business teams, manages high-volume contract workflows, improves templates and playbooks, and supports contract lifecycle processes and legal projects. The role requires strong commercial judgment, communication, negotiation skills, and the ability to balance legal risk with business objectives in a fast-growing technology company.

Own Snorkel’s Agentic Data and Reinforcement Learning Environments product roadmap. Define data product strategy, shape new product areas, and collaborate with research, academic partners, go-to-market, and operations teams. The role requires deep AI/ML and LLM post-training knowledge, experience building data products and technical roadmaps, customer discovery with technical buyers, quantitative market and unit-economic analysis, and strong influence across research-oriented stakeholders.

Leads Snorkel AI’s GTM systems strategy, Salesforce architecture, data governance, automation, and AI transformation. Manages a technical systems team, owns the GTM technology roadmap and vendor relationships, improves lead-to-cash processes, and partners across Sales, Delivery, Marketing, Finance, Legal, and Customer Success. The role drives scalable workflows, reliable revenue data, AI-enabled pipeline and forecasting solutions, and technology adoption across the organization.

Build infrastructure for large-scale AI and agentic workloads, including synthetic data generation, evaluation, orchestration, distributed compute, simulation environments, LLM routing, observability, and developer tooling. The role requires operating nondeterministic AI systems in production, improving reproducibility and reliability, and leading complex engineering initiatives across research, product, and engineering teams.

Build and deliver computer-use agent environments, datasets, evaluators, verifiers, and production solutions for AI labs and enterprise customers. Lead technical engagements from discovery through implementation and delivery, diagnose agent failures, run experiments, and improve reliability and performance. Partner with customers and internal engineering, research, and product teams while creating reusable frameworks, tooling, standards, and technical best practices. Provide technical leadership and communicate tradeoffs and recommendations to stakeholders.

Lead and scale Snorkel AI's technical recruiting function: build and manage a team of recruiters and sourcers, own hiring strategy and operating model, partner with technical leaders, design sourcing and pipeline strategies, use data to optimize hiring metrics, coach interviewers, and represent the company externally to attract top technical and AI talent.

The Senior Product Manager will lead development for AI data systems, ensuring product quality, improving workflows, and collaborating with cross-functional teams to deliver scalable solutions.

Maintain SOC 2 Type I and Type II compliance, coordinate audits and remediation, automate evidence collection through Vanta and Drata, manage access reviews and policy governance, support customer security questionnaires, and align controls with NIST, FedRAMP, and CMMC requirements. Partner with engineering and security teams on compliance-as-code, cloud controls, vendor risk management, metrics, incident evidence preservation, and federal readiness.

Build and maintain internal IT infrastructure as a product through automation, identity and access management, endpoint lifecycle management, networking, API integrations, workflow orchestration, internal tools, AI integrations, security scripting, alerting, and compliance automation. The role emphasizes Python or JavaScript development, Okta or Azure AD, MDM platforms, REST or GraphQL APIs, and security-first engineering practices.

Lead the Forward Deployed Engineering function, overseeing technical execution of data services and building a high-performing engineering team focused on AI data pipelines and workflows.

Lead and build TA operations: own recruiting tech stack and ATS, design scalable processes, reporting, and SLAs, use data and AI to improve hiring speed and quality, manage stakeholder partnerships and vendor integrations, and ensure data integrity across recruiting systems.

The Senior/Staff Research Scientist will develop and implement AI techniques, prototype solutions, and collaborate with teams to apply research in real-world settings.

Recruit Product talent for a high-growth AI startup by developing sourcing strategies, building diverse pipelines, analyzing recruiting metrics, delivering excellent candidate experiences, partnering with hiring managers, monitoring market trends, managing interview processes, and supporting onboarding and immigration. The role requires strong startup recruiting expertise, Product talent market knowledge, stakeholder coaching skills, and proficiency with modern recruiting tools.

Build and operate platform infrastructure, backend services, agent infrastructure, event-driven data pipelines, governance systems, CI/CD frameworks, and observability tooling. The role includes designing distributed systems on AWS, enforcing RBAC and compliance controls, optimizing infrastructure costs, defining reliability standards, participating in on-call, and leading complex engineering initiatives across teams.

Senior Technical Recruiter responsible for developing engineering recruiting strategies, sourcing passive candidates, managing pipelines, delivering excellent candidate experiences, partnering with engineering hiring managers, analyzing recruiting metrics, monitoring talent markets, coordinating interviews, improving hiring processes, and supporting onboarding and immigration. The role requires extensive full-cycle startup recruiting experience focused on software, AI/ML, and infrastructure engineering.

Build and maintain end-to-end product features across React and TypeScript front ends, APIs, and supporting services. Collaborate with product, design, and engineering teams to simplify complex workflows, make architecture decisions, improve accessibility and performance, and troubleshoot production issues. The role requires strong product judgment, full-stack fluency, independent decision-making, and effective cross-functional communication. Work is hybrid, requiring at least three days weekly in San Francisco or New York City.

Lead operational clarity and alignment within the Delivery organization, drive cross-functional initiatives, and ensure execution of strategic OKRs. Manage planning cycles and address risks proactively while improving processes and systems for efficiency.

The Senior Business Operations Manager will lead cross-functional initiatives, drive structured decision-making, and develop measurable outcomes to support business growth.